In recent years, in an image pickup device such as a digital steel camera or a digital video camera, needs for automatic recognition of an object whose image is to be captured are increasing. Such needs are for obtaining an optimum image. For example, there is a digital camera that has a function to automatically detect a human face and adjust a focus and/or exposure so that the focus and/or exposure is optimum for the detected human face.
Further, in capturing an image by a camera, there are many chances in which an animal such as a pet is an object whose image is to be captured. Accordingly, as in detection of a human face, a function to automatically detect an animal whose image is to be captured and to correct a focus and/or exposure is required.
Though the current technique has reached a practical level in a technique for detection of a human face, a technique for detecting an animal other than a human being is limited. The following appears to be one reason for this situation. That is, in a case where some object whose image is to be captured is to be detected, first, it is required to define characteristics of the object in advance. In regard to this point, human faces have many common characteristics and therefore are easily defined. On the other hand, as compared to human beings, animals are diverse, and it is difficult to define characteristics of animals in advance. For example, a case where a dog is to be defined is considered here. Though classified into one kind, i.e., “dog”, dogs differ from one another in shapes of faces and bodies, colors, lengths of hairs, shapes of ears depending on kinds. The difference between dogs is greater than difference between human beings. Therefore, it is difficult to define characteristics of dogs in advance. Consequently, it is difficult to automatically detect dogs that cannot be defined in advance. Further, in consideration of a situation in which an image is captured, unlike human beings, animals do not always face front toward a person who is to capture the image. Animals may face in various directions and take various poses. This point also makes automatic recognition of animals technically more difficult.
The followings are techniques for automatic recognition of an object. Patent Literature 1 discloses a technique to perform various processes based on information of a recognized object whose image is to be captured, in an electronic camera including a function of face recognition.
Patent Literature 2 discloses a technique to detect a position at which an object is present, a type of the object, and a rough distance to the object. The detection is carried out by inputting images captured by a plurality of cameras into one common image processing device and checking the images captured by the cameras with model data registered in a database in the image processing device.
Further, Patent Literature 3 describes a technique according to which a change in appearance of an object is predicted so that a model is formed, and input image information is checked with model data.
Patent Literature 4 discloses a technique in an image recognition device that detects a detection object that is present in an observation space according to which technique, in a case where a change occurs in a background image and an input image, it is determined whether or not the change is caused by a small animal by use of a small animal indicator.
Patent Literature 5 discloses a technique according to which a car is recognized by thermal imaging and a type of the car is determined/classified.
Patent Literature 6 discloses a technique for creating information for identifying an animal by extracting an outline of a nose and respective outlines of two nostrils from an image of a whole nose of the animal.